OpSeF : Open Source Python Framework for Collaborative Instance Segmentation of Bioimages

Various pre-trained deep learning models for the segmentation of bioimages have been made available as developer-to-end-user solutions. They are optimized for ease of use and usually require neither knowledge of machine learning nor coding skills. However, individually testing these tools is tedious and success is uncertain. Here, we present the Open Segmentation Framework (OpSeF), a Python framework for deep learning-based instance segmentation. OpSeF aims at facilitating the collaboration of biomedical users with experienced image analysts. It builds on the analysts' knowledge in Python, machine learning, and workflow design to solve complex analysis tasks at any scale in a reproducible, well-documented way. OpSeF defines standard inputs and outputs, thereby facilitating modular workflow design and interoperability with other software. Users play an important role in problem definition, quality control, and manual refinement of results. OpSeF semi-automates preprocessing, convolutional neural network (CNN)-based segmentation in 2D or 3D, and postprocessing. It facilitates benchmarking of multiple models in parallel. OpSeF streamlines the optimization of parameters for pre- and postprocessing such, that an available model may frequently be used without retraining. Even if sufficiently good results are not achievable with this approach, intermediate results can inform the analysts in the selection of the most promising CNN-architecture in which the biomedical user might invest the effort of manually labeling training data. We provide Jupyter notebooks that document sample workflows based on various image collections. Analysts may find these notebooks useful to illustrate common segmentation challenges, as they prepare the advanced user for gradually taking over some of their tasks and completing their projects independently. The notebooks may also be used to explore the analysis options available within OpSeF in an interactive way and to document and share final workflows. Currently, three mechanistically distinct CNN-based segmentation methods, the U-Net implementation used in Cellprofiler 3.0, StarDist, and Cellpose have been integrated within OpSeF. The addition of new networks requires little; the addition of new models requires no coding skills. Thus, OpSeF might soon become both an interactive model repository, in which pre-trained models might be shared, evaluated, and reused with ease.Peer reviewe

In vivo Imaging of Intact Drosophila Larvae at Sub-cellular Resolution

Recent improvements in optical imaging, genetically encoded fluorophores and genetic tools allowing efficient establishment of desired transgenic animal lines have enabled biological processes to be studied in the context of a living, and in some instances even behaving, organism. In this protocol we will describe how to anesthetize intact Drosophila larvae, using the volatile anesthetic desflurane, to follow the development and plasticity of synaptic populations at sub-cellular resolution1-3. While other useful methods to anesthetize Drosophila melanogaster larvae have been previously described4,5,6,7,8, the protocol presented herein demonstrates significant improvements due to the following combined key features: (1) A very high degree of anesthetization; even the heart beat is arrested allowing for lateral resolution of up to 150 nm1, (2) a high survival rate of > 90% per anesthetization cycle, permitting the recording of more than five time-points over a period of hours to days2 and (3) a high sensitivity enabling us in 2 instances to study the dynamics of proteins expressed at physiological levels. In detail, we were able to visualize the postsynaptic glutamate receptor subunit GluR-IIA expressed via the endogenous promoter1 in stable transgenic lines and the exon trap line FasII-GFP1. (4) In contrast to other methods4,7 the larvae can be imaged not only alive, but also intact (i.e. non-dissected) allowing observation to occur over a number of days1. The accompanying video details the function of individual parts of the in vivo imaging chamber2,3, the correct mounting of the larvae, the anesthetization procedure, how to re-identify specific positions within a larva and the safe removal of the larvae from the imaging chamber

The Ig cell adhesion molecule Basigin controls compartmentalization and vesicle release at Drosophila melanogaster synapses

Synapses can undergo rapid changes in size as well as in their vesicle release function during both plasticity processes and development. This fundamental property of neuronal cells requires the coordinated rearrangement of synaptic membranes and their associated cytoskeleton, yet remarkably little is known of how this coupling is achieved. In a GFP exon-trap screen, we identified Drosophila melanogaster Basigin (Bsg) as an immunoglobulin domain-containing transmembrane protein accumulating at periactive zones of neuromuscular junctions. Bsg is required pre- and postsynaptically to restrict synaptic bouton size, its juxtamembrane cytoplasmic residues being important for that function. Bsg controls different aspects of synaptic structure, including distribution of synaptic vesicles and organization of the presynaptic cortical actin cytoskeleton. Strikingly, bsg function is also required specifically within the presynaptic terminal to inhibit nonsynchronized evoked vesicle release. We thus propose that Bsg is part of a transsynaptic complex regulating synaptic compartmentalization and strength, and coordinating plasma membrane and cortical organization

Cell Wall Amidase AmiC1 Is Required for Cellular Communication and Heterocyst Development in the Cyanobacterium Anabaena PCC 7120 but Not for Filament Integrity

Filamentous cyanobacteria of the order Nostocales display typical properties of multicellular organisms. In response to nitrogen starvation, some vegetative cells differentiate into heterocysts, where fixation of N(2) takes place. Heterocysts provide a micro-oxic compartment to protect nitrogenase from the oxygen produced by the vegetative cells. Differentiation involves fundamental remodeling of the Gram-negative cell wall by deposition of a thick envelope and by formation of a neck-like structure at the contact site to the vegetative cells. Cell wall-hydrolyzing enzymes, like cell wall amidases, are involved in peptidoglycan maturation and turnover in unicellular bacteria. Recently, we showed that mutation of the amidase homologue amiC2 gene in Nostoc punctiforme ATCC 29133 distorts filament morphology and function. Here, we present the functional characterization of two amiC paralogues from Anabaena sp. strain PCC 7120. The amiC1 (alr0092) mutant was not able to differentiate heterocysts or to grow diazotrophically, whereas the amiC2 (alr0093) mutant did not show an altered phenotype under standard growth conditions. In agreement, fluorescence recovery after photobleaching (FRAP) studies showed a lack of cell-cell communication only in the AmiC1 mutant. Green fluorescent protein (GFP)-tagged AmiC1 was able to complement the mutant phenotype to wild-type properties. The protein localized in the septal regions of newly dividing cells and at the neck region of differentiating heterocysts. Upon nitrogen step-down, no mature heterocysts were developed in spite of ongoing heterocyst-specific gene expression. These results show the dependence of heterocyst development on amidase function and highlight a pivotal but so far underestimated cellular process, the remodeling of peptidoglycan, for the biology of filamentous cyanobacteria

The Kinesin-3, Unc-104 Regulates Dendrite Morphogenesis and Synaptic Development in Drosophila

Kinesin-based transport is important for synaptogenesis, neuroplasticity, and maintaining synaptic function. In an anatomical screen of neurodevelopmental mutants, we identified the exchange of a conserved residue (R561H) in the forkhead-associated domain of the kinesin-3 family member Unc-104/KIF1A as the genetic cause for defects in synaptic terminal- and dendrite morphogenesis. Previous structure-based analysis suggested that the corresponding residue in KIF1A might be involved in stabilizing the activated state of kinesin-3 dimers. Herein we provide the first in vivo evidence for the functional importance of R561. The R561H allele (unc-104(bris)) is not embryonic lethal, which allowed us to investigate consequences of disturbed Unc-104 function on postembryonic synapse development and larval behavior. We demonstrate that Unc-104 regulates the reliable apposition of active zones and postsynaptic densities, possibly by controlling site-specific delivery of its cargo. Next, we identified a role for Unc-104 in restraining neuromuscular junction growth and coordinating dendrite branch morphogenesis, suggesting that Unc-104 is also involved in dendritic transport. Mutations in KIF1A/unc-104 have been associated with hereditary spastic paraplegia and hereditary sensory and autonomic neuropathy type 2. However, we did not observe synapse retraction or dystonic posterior paralysis. Overall, our study demonstrates the specificity of defects caused by selective impairments of distinct molecular motors and highlights the critical importance of Unc-104 for the maturation of neuronal structures during embryonic development, larval synaptic terminal outgrowth, and dendrite morphogenesis